6 from cwltool.process import get_feature, shortname
7 from cwltool.errors import WorkflowException
8 from cwltool.draft2tool import revmap_file, CommandLineTool
9 from cwltool.load_tool import fetch_document
10 from cwltool.builder import Builder
12 import arvados.collection
14 from .arvdocker import arv_docker_get_image
15 from .runner import Runner
16 from .pathmapper import InitialWorkDirPathMapper
17 from .perf import Perf
20 logger = logging.getLogger('arvados.cwl-runner')
22 tmpdirre = re.compile(r"^\S+ \S+ \d+ \d+ stderr \S+ \S+ crunchrunner: \$\(task\.tmpdir\)=(.*)")
23 outdirre = re.compile(r"^\S+ \S+ \d+ \d+ stderr \S+ \S+ crunchrunner: \$\(task\.outdir\)=(.*)")
24 keepre = re.compile(r"^\S+ \S+ \d+ \d+ stderr \S+ \S+ crunchrunner: \$\(task\.keep\)=(.*)")
26 class ArvadosJob(object):
27 """Submit and manage a Crunch job for executing a CWL CommandLineTool."""
29 def __init__(self, runner):
30 self.arvrunner = runner
34 def run(self, dry_run=False, pull_image=True, **kwargs):
36 "command": self.command_line
38 runtime_constraints = {}
40 if self.generatefiles["listing"]:
41 vwd = arvados.collection.Collection()
42 script_parameters["task.vwd"] = {}
43 generatemapper = InitialWorkDirPathMapper([self.generatefiles], "", "",
45 for f, p in generatemapper.items():
46 if p.type == "CreateFile":
47 with vwd.open(p.target, "w") as n:
48 n.write(p.resolved.encode("utf-8"))
50 for f, p in generatemapper.items():
52 script_parameters["task.vwd"][p.target] = p.resolved
53 if p.type == "CreateFile":
54 script_parameters["task.vwd"][p.target] = "$(task.keep)/%s/%s" % (vwd.portable_data_hash(), p.target)
56 script_parameters["task.env"] = {"TMPDIR": self.tmpdir, "HOME": self.outdir}
58 script_parameters["task.env"].update(self.environment)
61 script_parameters["task.stdin"] = self.stdin
64 script_parameters["task.stdout"] = self.stdout
67 script_parameters["task.stderr"] = self.stderr
70 script_parameters["task.successCodes"] = self.successCodes
71 if self.temporaryFailCodes:
72 script_parameters["task.temporaryFailCodes"] = self.temporaryFailCodes
73 if self.permanentFailCodes:
74 script_parameters["task.permanentFailCodes"] = self.permanentFailCodes
76 (docker_req, docker_is_req) = get_feature(self, "DockerRequirement")
77 if docker_req and kwargs.get("use_container") is not False:
78 runtime_constraints["docker_image"] = arv_docker_get_image(self.arvrunner.api, docker_req, pull_image, self.arvrunner.project_uuid)
80 runtime_constraints["docker_image"] = "arvados/jobs"
82 resources = self.builder.resources
83 if resources is not None:
84 runtime_constraints["min_cores_per_node"] = resources.get("cores", 1)
85 runtime_constraints["min_ram_mb_per_node"] = resources.get("ram")
86 runtime_constraints["min_scratch_mb_per_node"] = resources.get("tmpdirSize", 0) + resources.get("outdirSize", 0)
88 filters = [["repository", "=", "arvados"],
89 ["script", "=", "crunchrunner"],
90 ["script_version", "in git", "9e5b98e8f5f4727856b53447191f9c06e3da2ba6"]]
91 if not self.arvrunner.ignore_docker_for_reuse:
92 filters.append(["docker_image_locator", "in docker", runtime_constraints["docker_image"]])
95 with Perf(logger, "create %s" % self.name):
96 response = self.arvrunner.api.jobs().create(
98 "owner_uuid": self.arvrunner.project_uuid,
99 "script": "crunchrunner",
100 "repository": "arvados",
101 "script_version": "master",
102 "minimum_script_version": "9e5b98e8f5f4727856b53447191f9c06e3da2ba6",
103 "script_parameters": {"tasks": [script_parameters]},
104 "runtime_constraints": runtime_constraints
107 find_or_create=kwargs.get("enable_reuse", True)
108 ).execute(num_retries=self.arvrunner.num_retries)
110 self.arvrunner.processes[response["uuid"]] = self
112 self.update_pipeline_component(response)
114 logger.info("Job %s (%s) is %s", self.name, response["uuid"], response["state"])
116 if response["state"] in ("Complete", "Failed", "Cancelled"):
117 with Perf(logger, "done %s" % self.name):
119 except Exception as e:
120 logger.error("Got error %s" % str(e))
121 self.output_callback({}, "permanentFail")
123 def update_pipeline_component(self, record):
124 if self.arvrunner.pipeline:
125 self.arvrunner.pipeline["components"][self.name] = {"job": record}
126 with Perf(logger, "update_pipeline_component %s" % self.name):
127 self.arvrunner.pipeline = self.arvrunner.api.pipeline_instances().update(uuid=self.arvrunner.pipeline["uuid"],
129 "components": self.arvrunner.pipeline["components"]
130 }).execute(num_retries=self.arvrunner.num_retries)
131 if self.arvrunner.uuid:
133 job = self.arvrunner.api.jobs().get(uuid=self.arvrunner.uuid).execute()
135 components = job["components"]
136 components[self.name] = record["uuid"]
137 self.arvrunner.api.jobs().update(uuid=self.arvrunner.uuid,
139 "components": components
140 }).execute(num_retries=self.arvrunner.num_retries)
141 except Exception as e:
142 logger.info("Error adding to components: %s", e)
144 def done(self, record):
146 self.update_pipeline_component(record)
151 if record["state"] == "Complete":
152 processStatus = "success"
154 processStatus = "permanentFail"
159 with Perf(logger, "inspect log %s" % self.name):
160 logc = arvados.collection.Collection(record["log"])
161 log = logc.open(logc.keys()[0])
166 # Determine the tmpdir, outdir and keepdir paths from
167 # the job run. Unfortunately, we can't take the first
168 # values we find (which are expected to be near the
169 # top) and stop scanning because if the node fails and
170 # the job restarts on a different node these values
171 # will different runs, and we need to know about the
172 # final run that actually produced output.
174 g = tmpdirre.match(l)
177 g = outdirre.match(l)
184 with Perf(logger, "output collection %s" % self.name):
185 outputs = done.done(self, record, tmpdir, outdir, keepdir)
186 except WorkflowException as e:
187 logger.error("Error while collecting job outputs:\n%s", e, exc_info=(e if self.arvrunner.debug else False))
188 processStatus = "permanentFail"
190 except Exception as e:
191 logger.exception("Got unknown exception while collecting job outputs:")
192 processStatus = "permanentFail"
195 self.output_callback(outputs, processStatus)
197 del self.arvrunner.processes[record["uuid"]]
200 class RunnerJob(Runner):
201 """Submit and manage a Crunch job that runs crunch_scripts/cwl-runner."""
203 def arvados_job_spec(self, dry_run=False, pull_image=True, **kwargs):
204 """Create an Arvados job specification for this workflow.
206 The returned dict can be used to create a job (i.e., passed as
207 the +body+ argument to jobs().create()), or as a component in
208 a pipeline template or pipeline instance.
211 workflowmapper = super(RunnerJob, self).arvados_job_spec(dry_run=dry_run, pull_image=pull_image, **kwargs)
213 self.job_order["cwl:tool"] = workflowmapper.mapper(self.tool.tool["id"]).target[5:]
215 "script": "cwl-runner",
216 "script_version": "master",
217 "repository": "arvados",
218 "script_parameters": self.job_order,
219 "runtime_constraints": {
220 "docker_image": "arvados/jobs"
224 def run(self, *args, **kwargs):
225 job_spec = self.arvados_job_spec(*args, **kwargs)
226 job_spec.setdefault("owner_uuid", self.arvrunner.project_uuid)
228 response = self.arvrunner.api.jobs().create(
230 find_or_create=self.enable_reuse
231 ).execute(num_retries=self.arvrunner.num_retries)
233 self.uuid = response["uuid"]
234 self.arvrunner.processes[self.uuid] = self
236 logger.info("Submitted job %s", response["uuid"])
238 if kwargs.get("submit"):
239 self.arvrunner.pipeline = self.arvrunner.api.pipeline_instances().create(
241 "owner_uuid": self.arvrunner.project_uuid,
242 "name": shortname(self.tool.tool["id"]),
243 "components": {"cwl-runner": {"job": {"uuid": self.uuid, "state": response["state"]} } },
244 "state": "RunningOnClient"}).execute(num_retries=self.arvrunner.num_retries)
246 if response["state"] in ("Complete", "Failed", "Cancelled"):
250 class RunnerTemplate(object):
251 """An Arvados pipeline template that invokes a CWL workflow."""
253 type_to_dataclass = {
254 'boolean': 'boolean',
256 'Directory': 'Collection',
262 def __init__(self, runner, tool, job_order, enable_reuse):
265 self.job = RunnerJob(
269 enable_reuse=enable_reuse)
271 def pipeline_component_spec(self):
272 """Return a component that Workbench and a-r-p-i will understand.
274 Specifically, translate CWL input specs to Arvados pipeline
275 format, like {"dataclass":"File","value":"xyz"}.
277 spec = self.job.arvados_job_spec()
279 # Most of the component spec is exactly the same as the job
280 # spec (script, script_version, etc.).
281 # spec['script_parameters'] isn't right, though. A component
282 # spec's script_parameters hash is a translation of
283 # self.tool.tool['inputs'] with defaults/overrides taken from
284 # the job order. So we move the job parameters out of the way
285 # and build a new spec['script_parameters'].
286 job_params = spec['script_parameters']
287 spec['script_parameters'] = {}
289 for param in self.tool.tool['inputs']:
290 param = copy.deepcopy(param)
292 # Data type and "required" flag...
293 types = param['type']
294 if not isinstance(types, list):
296 param['required'] = 'null' not in types
297 non_null_types = set(types) - set(['null'])
298 if len(non_null_types) == 1:
299 the_type = [c for c in non_null_types][0]
300 dataclass = self.type_to_dataclass.get(the_type)
302 param['dataclass'] = dataclass
303 # Note: If we didn't figure out a single appropriate
304 # dataclass, we just left that attribute out. We leave
305 # the "type" attribute there in any case, which might help
308 # Title and description...
309 title = param.pop('label', '')
310 descr = param.pop('doc', '').rstrip('\n')
312 param['title'] = title
314 param['description'] = descr
316 # Fill in the value from the current job order, if any.
317 param_id = shortname(param.pop('id'))
318 value = job_params.get(param_id)
321 elif not isinstance(value, dict):
322 param['value'] = value
323 elif param.get('dataclass') in ('File', 'Collection') and value.get('location'):
324 param['value'] = value['location'][5:]
326 spec['script_parameters'][param_id] = param
327 spec['script_parameters']['cwl:tool'] = job_params['cwl:tool']
331 job_spec = self.pipeline_component_spec()
332 response = self.runner.api.pipeline_templates().create(body={
334 self.job.name: job_spec,
336 "name": self.job.name,
337 "owner_uuid": self.runner.project_uuid,
338 }, ensure_unique_name=True).execute(num_retries=self.runner.num_retries)
339 self.uuid = response["uuid"]
340 logger.info("Created template %s", self.uuid)